Ordinamento stocastico basato sulle permutazioni utilizzando confronti a coppie

Mattiello, Federico (2015) Ordinamento stocastico basato sulle permutazioni utilizzando confronti a coppie, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Metodologia statistica per la ricerca scientifica, 26 Ciclo. DOI 10.6092/unibo/amsdottorato/6735.
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Abstract

The topic of this work concerns nonparametric permutation-based methods aiming to find a ranking (stochastic ordering) of a given set of groups (populations), gathering together information from multiple variables under more than one experimental designs. The problem of ranking populations arises in several fields of science from the need of comparing G>2 given groups or treatments when the main goal is to find an order while taking into account several aspects. As it can be imagined, this problem is not only of theoretical interest but it also has a recognised relevance in several fields, such as industrial experiments or behavioural sciences, and this is reflected by the vast literature on the topic, although sometimes the problem is associated with different keywords such as: "stochastic ordering", "ranking", "construction of composite indices" etc., or even "ranking probabilities" outside of the strictly-speaking statistical literature. The properties of the proposed method are empirically evaluated by means of an extensive simulation study, where several aspects of interest are let to vary within a reasonable practical range. These aspects comprise: sample size, number of variables, number of groups, and distribution of noise/error. The flexibility of the approach lies mainly in the several available choices for the test-statistic and in the different types of experimental design that can be analysed. This render the method able to be tailored to the specific problem and the to nature of the data at hand. To perform the analyses an R package called SOUP (Stochastic Ordering Using Permutations) has been written and it is available on CRAN.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Mattiello, Federico
Supervisore
Co-supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze economiche e statistiche
Ciclo
26
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Stochastic ordering, Permutation test, Nonparametric combination methodology, Pairwise comparisons, Multivariate analysis
URN:NBN
DOI
10.6092/unibo/amsdottorato/6735
Data di discussione
2 Febbraio 2015
URI

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